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linear and quadratic multiple regressions analysis on magneto-thermal and chemical reactions on the Casson-Williamson nanofluids boundary layer flow under Soret-Dufour mechanism

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Arab Journal of Basic and Applied Sciences 2022年第1期29卷 269-286页

作者： Falodun, B.O. Ige, E.O. Department of Computer Science/Mathematics Novena University Delta State Ogume Nigeria Department of Mechanical and Mechatronics Engineering Afe Babalola University Ado-Ekiti Nigeria Biomedical Engineering Afe Babalola University Ado-Ekiti Nigeria

The focus of this paper is to conduct research on MHD Casson-Williamson nanofluids flow over an inclined plate with the influence of thermal radiation and Soret-Dufour mechanisms using spectral collocation and statistical analysis. The simultaneous flow of Casson-Williamson non-Newtonian fluids in the presence of a magnetic field, Joule heating, chemical reaction, and viscous dissipation is modelled by utilizing partial differential equations (PDEs). These equations were transformed into coupled nonlinear ordinary differential equations by using an appropriate similarity variable. A numerical and statistical analysis was performed on the transformed equations to obtain significant effects of flow parameters on velocity, temperature, and concentration distributions. An increase in the value of the thermal radiation is observed to increase the fluid temperature, thermal condition, and thermal boundary layer thickness. An increased value of magnetic parameter was observed to decrease the fluid velocity. Due to a magnetic field and the dynamic plastic viscosity, the hydrodynamic boundary layer was observed to decline due to an increase in Casson parameter. The present study was compared with studies in the literature and found in good agreement. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the University of Bahrain.

关键词： Casson nanofluids Dufuor mechanism linear regression analysis multiple-quadratic regression analysis Rosseland approximation spectral collocation method

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A high-precision measurement method for moment of inertia based on torsion pendulum method

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MEASUREMENT SCIENCE AND TECHNOLOGY 2024年第12期35卷 125013-125013页

作者： Cui, Haichao Hong, Yanji Du, Baosheng Han, Jianhui Wang, Linyan Ye, Jifei Wang, Diankai Space Engn Univ Dept Aerosp Sci & Technol State Key Lab Laser Prop & Applicat Beijing 101416 Peoples R China

The precise determination of moment of inertia (MOI) holds paramount importance in investigating the rotational dynamics of an object. Based on the torsion pendulum system, a novel high-precision measurement method for MOI is developed by using the constant force in this paper. Firstly, the extreme response characteristics of a torsional pendulum measurement system under a constant force are discussed in detail in this paper, and the relationships between the system damping ratio, natural frequency, MOI and the extremal characteristic points of the system response are determined through the linear regression analysis. By applying the superposition principle, the MOI for the object being measured can be computed. As the performance of the constant force source is the key to ensure the measurement accuracy, this paper develops an electromagnetic force source, which consists of a coil and a permanent magnet, and the electromagnetic force variation law with the relative position of the coil and permanent magnet is investigated by utilizing a high-precision electronic balance, and then the optimal relative position is determined to reduce the impact of the relative position on the electromagnetic force. Furthermore, the high-precision electromagnetic force driving equation at the optimal position is acquired by utilizing the least square method. Finally, this paper develops a novel torsional measurement device for the MOI and successfully achieves high-precise measurement of the MOI for the target object using the proposed measurement method. The measurement experiment for MOI of a target object indicates that the corresponding measurement relative error is 0.297%, thereby confirming the effectiveness and high precision of the proposed measurement approach.

关键词： moment of inertia torsion pendulum system electromagnetic constant force parameter identification linear regression analysis

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Flexible multimode pressure sensor based on liquid metal

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SMART STRUCTURES AND SYSTEMS 2021年第6期28卷 839-853页

作者： Zhou, Xiaoping Yu, Zihao Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China

In this paper, a novel multimode liquid metal-based pressure sensor is developed. The main body of the sensor is composed of polydimethylsiloxane (PDMS) elastomer. The structure of the sensor looks like a sandwich, in which the upper structure contains a cylindrical cavity, and the bottom structure contains a spiral microchannel, and the middle partition layer separates the upper and the bottom structures. Then, the liquid metal is injected into the top cavity and the bottom microchannel. Based on linear elastic fracture mechanics, the deformation of the microchannel cross-section is theoretically analyzed. The changes of resistance, capacitance, and inductance of the microchannel under pressure are deduced, and the corresponding theoretical models are established. The theoretical values of the pressure sensor are in good agreement with experimental data, implying that the developed theoretical model can explain the performance of the sensor well.

关键词： linear regression analysis liquid metal multimode pressure sensor

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Research on modeling the thixotropic properties of cementitious systems using regression methods in machine learning

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CONSTRUCTION AND BUILDING MATERIALS 2024年 411卷

作者： Sahin, Hatice Gizem Altun, Oznur Biricik Eser, Murat Mardani, Ali Bilgin, Metin Bursa Uludag Univ Fac Engn Dept Civil Engn Bursa Turkiye Bursa Uludag Univ Fac Engn Dept Comp Engn Bursa Turkiye

In this study, the rheological properties of cementitious systems were investigated through modeling studies on structural build-up and breakdown area. The area values were calculated using Herschel Bulkley analysis and hysteresis area method. The properties were examined by varying the composition of the cementitious system (cement fineness, C4AF, C3S, C2S, C3A, equivalent alkali and metakaolin ratio) and changes made in the rheological measurement processes (applied shear rate, maximum shear rate and duration). For this purpose, cement paste mixtures were prepared by substituting metakaolin at four different ratios (3%, 6%, 9%, and 12%) into cements with varying C3A content (2.13, 3.60, 6.82, 9.05%). The modeling study of the obtained results was conducted using three different learning methods: linear regression analysis (LR), AdaBoost, and K Nearest Neighbor (KNN), encompassing machine learning and ensemble learning techniques. It was determined that the most dominant parameter affecting the rheology and thixotropic properties of the mixtures is the metakaolin usage ratio. The pre-shear rate was dominant over the duration and maximum shear rate parameters. Effect of the C3A content on dynamic yield stress and viscosity becomes more pronounced with an increase in the applied shear rate. The KNN method has yielded the best results in all experimental modeling studies. Euclidean distance criterion was used in the KNN method. Although the AdaBoost method obtained results close to the KNN method, the opposite situation was observed depending on the number of data. Logcosh, MAE and RMSE metrics were used to evaluate the experimental results. When the results for 3 different metrics in all modeling studies were examined, the success order of the metrics was found to be Logcosh, MAE and RMSE.

关键词： Dynamic yield stress Structural build-up/breakdown area linear regression analysis AdaBoost K nearest neighbor

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Performance analysis of geomembrane subjected under elevated temperatures

Performance analysis of geomembrane subjected under elevated...

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International Conference on Advances in Materials Science (ICAMS)

作者： Bhavani, V. Nikhila Sangeetha, S. VNR VJIET Dept Civil Engn Hyderabad 500090 Telangana India

A macro-level analysis has been carried out using linear regression analysis in MS Excel to determine the half-life of Geomembrane (GM) when it is being exposed to higher temperatures. Four different GM were taken for the study and it is observed that the SCR of GM is high at 105 degrees C, 115 degrees C when compared to 95 degrees C, this may be due to annealing effect as it increases the thickness of GM thereby SCR of GM has increased. Half-life observed for GM 1 is 2.5, 1, 0.68 years at 95 degrees C, 105 degrees C, 115 degrees C respectively, for GM 2 is 1.8, 1, 0.5 years at 95 degrees C, 105 degrees C, 115 degrees C, for GM 3 is1.7, 1, 0.5 years at 95 degrees C, 105 degrees C, 115 degrees C & for GM 4 is 1.8, 0.5 years at 105 degrees C, 115 degrees C. It is observed that GM subjected to higher temperature has a greater effect on it. Exposure of GM to elevated temperature closure to its melting point has reduced its durability significantly. Copyright (C) 2022 Elsevier Ltd. All rights reserved.

关键词： Stress Crack Resistance Geomembrane Landfill Half-life Temperature linear regression analysis

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Mathematical modelling for predicting mechanical properties in rebar manufacturing

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IRONMAKING & STEELMAKING 2021年第2期48卷 161-169页

作者： Murta, Raphaella H. F. Braga, Fabricio D. Maia, Pedro P. N. Diogenes, Otilio B. F. de Moura, Elineudo P. Univ Fed Ceara Dept Met & Mat Engn Bloco 729 BR-60440554 Fortaleza Ceara Brazil

The mechanical properties of steel depend strongly on chemical composition and the parameters used during thermomechanical processing. Understanding how each variable affects such properties is indispensable for obtaining high-quality steel products at a lower cost. However, the large number of variables involved in the manufacturing process makes this a difficult task. It is possible to use statistical tools combined with predictive modelling to identify the most relevant parameters and to create a mathematical function that can adequately describe the mechanical properties of the rebar from the selected input-output pairs. In the present work, information about the chemical composition and the thermomechanical processing variables were collected at steel mills and used to predict the mechanical properties of rebar using linear regression analysis and an artificial neural networks approach. The coefficient of determination between the measured and estimated values was calculated for yield strength (YS), ultimate tensile strength (UTS), UTS/YS ratio, and percent elongation. The estimation performed using the artificial neural network was better than the one calculated by linear regression analysis for all four properties studied. The results showed that an artificial neural network can be useful in evaluating and choosing the most adequate parameters to achieve the desired steel properties.

关键词： Steel mechanical properties statistical tools linear regression analysis artificial neural networks

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Evaluating the association between lifestyle factors and heel bone mineral density in different inflammatory states

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HELIYON 2024年第13期10卷 e33435页

作者： Feng, Ruoyang Cheng, Shiqiang Zhang, Feng Xu, Ke Liu, Lin Yang, Mingyi Xu, Peng Xi An Jiao Tong Univ HongHui Hosp Dept Joint Surg Xian 710054 Shanxi Peoples R China Xi An Jiao Tong Univ Hlth Sci Ctr Sch Publ Hlth Key Lab Trace Elements & Endem DisNatl Hlth & Fa Xian 710061 Peoples R China

Rationale: It is unclear whether lifestyle factors affect bone mineral density (BMD) during different inflammatory states. Objective: This study investigated the effects of coffee consumption, vitamin D (VD) intake, smoking, and alcohol consumption on heel BMD in adults with different inflammatory states. Methods: The phenotypic data from 249,825 participants were analyzed using the UK Biobank cohort. The inflammatory status was evaluated using C-reactive protein (CRP) levels and the systemic immune-inflammation index. linear regression analysis was used to examine the association between coffee consumption, VD, smoking, alcohol consumption, and heel BMD in adults with different inflammatory states. linear regression models were used to analyze the interaction between inflammation and the four lifestyle factors with respect to their influence on heel BMD in adults. Results: Our findings revealed that VD was positively associated with adult heel BMD ((3 = 2.41 x 10- 2, SE = 5.14 x 10-3, P = 2.72 x 10-6), while alcohol consumption and smoking were negatively associated with adult heel BMD. Coffee was negatively associated with adult heel BMD in low inflammatory states ((3 = -1.27 x 10- 2, SE = 4.79 x 10-3, P = 8.00 x 10-3), while there was no association between coffee and adult heel BMD in high inflammatory states. Overall, it was found that these four lifestyle factors interacted negatively with inflammatory states. Conclusion: Our study suggests that VD is positively associated with adult heel BMD and that alcohol consumption and smoking are negatively associated with adult heel BMD. Coffee may reverse the adverse effects of inflammation on BMD when the patient is in a highly inflammatory state, thus acting as a protective agent against heel BMD in adults.

关键词： Heel bone mineral density C -reactive protein Systemic immunoinflammatory index Lifestyle linear regression analysis

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Modeling the Estimation Errors of Visual-based Systems Developed for Vehicle Speed Measurement

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第1期12卷 240-251页

作者： Alkherret, Abdulrazzaq Jawish AbuAddous, Musab Jerash Univ Fac Engn Dept Civil Engn Jerash Jordan Yarmouk Univ Hijjawi Fac Engn Technol Dept Civil Engn Irbid Jordan

This paper aims to modeling the relationship between the error of visual-based systems developed for vehicle speed estimation (as dependent variable) and each of the detection region length, the camera angle, and the volume-to-capacity ratio (V/C), as independent variables. Simulation software (VISSIM) is used to generate a set of video clips of predefined traffic based on different values of the dependent variables. These videos are analyzed with a video-based detection and tracking model (VBDATM) developed in 2015. Errors are expressed as differences between each of the actual speeds generated by VISSIM and the speeds computed by the VBDATM divided by the actual speed. The results conducted by the forward stepwise regression analysis show that the V/C ratio does not affect the accuracy of the estimate and there are weak relationships between the estimation error and each of camera position and the detection region length.

关键词： Intelligent transportation systems image processing vehicle detection vehicle tracking speed estimation traffic simulation linear regression analysis

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Composition and nutritional evaluation of amino acids in Mimai qu rice wines

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ITALIAN JOURNAL OF FOOD SCIENCE 2021年第2期33卷 46-53页

作者： Zhang, Kaizheng Wu, Wenchi Zou, Wei Kang, Zhenhui Yan, Qin Qin, Yue Sichuan Univ Sci & Engn Zigong City Sichuan Peoples R China Chengdu Inst Prod Qual Inspect Co Ltd Chengdu Peoples R China

An amino acid analyzer was used to detect free amino acids (FAA) in Mimai Qu rice wines (SMW and DMW) and control wine samples (Chinese rice wine [CRW] and Japanese sake [ JNS]). It was found that CRW had the highest total amino acid (TAA) content (similar to 2814 mg/L), followed by SMW (similar to 2509 mg/L) and DMW (similar to 1474 mg/L), while JNS had the least (similar to 917 mg/L). Amino acid ratio coefficient method (SRCAA), linear regression method, cluster analysis (CA) and principal component analysis (PCA) were used for evaluating the nutritional value of amino acids in wine samples, giving similar results. SMW had the highest nutritional value, followed by CRW and DMW and JNS.

关键词： brewed wine cluster analysis linear regression analysis principal component analysis ratio coefficient method

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Factors affecting medical students' satisfaction with online learning: a regression analysis of a survey

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BMC MEDICAL EDUCATION 2024年第1期24卷 11页

作者： Cakmakkaya, Ozlem Serpil Meydanli, Elif Guzel Kafadar, Ali Metin Demirci, Mehmet Selman Suzer, Oner Ar, Muhlis Cem Yaman, Muhittin Onur Demirbas, Kaan Can Gonen, Mustafa Sait Istanbul Univ Dept Med Biol Cerrahpasa Med Fac Fatih 34098 Kocamustafapasa Turkiye Kocaeli Univ Fac Med Dept Histol & Embryol Kocaeli Turkiye Sakarya Univ Med Fac Dept Neurosurg Sakarya Turkiye Istanbul Univ Cerrahpasa Med Fac Dept Orthoped & Traumatol Cerrahpasa Turkiye Biruni Univ Med Fac Dept Med Pharmacol Istanbul Turkiye Istanbul Univ Dept Internal Med Div Haematol Cerrahpasa Med Fac Istanbul Turkiye Ondokuz Mayis Univ Vocat Sch Hlth Serv Dept Med Serv & Tech Samsun Turkiye Istanbul Univ Cerrahpasa Med Fac Cerrahpasa Turkiye Hacettepe Univ Fac Med Dept Internal Med Div Endocrinol & Metab Ankara Turkiye

BackgroundMedical education requires the implementation of different teaching methods and strategies for future doctors to achieve broad learning objectives. This wide range of methods and strategies includes the use of Information Technologies. For a long time, there was a call for a change in medical education for blending new teaching approaches to lessen medical students' class time. The COVID-19 pandemic then sped up the transition to the new way of medical education and classroom lectures were quickly moved to a virtual environment. We expect that these changes will continue, and online learning will be one of the main teaching strategies in medical education. Therefore, educational experiences during the COVID-19 pandemic will improve our understanding of online learning and will help to develop blended medical school curricula in the future. For this reason, we aimed to determine students' overall satisfaction with their online learning experience and to define the main factors affecting students' satisfaction with their online learning program at Cerrahpasa Medical *** cross-sectional survey study was conducted to determine medical students' overall satisfaction with online learning methods and to identify factors associated with positive and negative satisfaction levels. A questionnaire, consisting of 24 questions to collect demographic characteristics, factors associated with online education experience and overall satisfaction levels was developed and distributed to 1600 medical students. Multivariable linear regression analysis was used to determine the factors associated with positive and negative satisfaction *** analysis showed that being familiar with online teaching techniques (beta = 0.19, 95% CI [0.07, 0.30], faculty members' higher online teaching skill levels (beta = 0.42, 95% CI [0.32, 0.51], interactive online teaching approaches (beta = 0.54, 95% CI [0.41, 0.67], having a personal workspace (beta = 0.43, 95%

关键词： Medical education Online learning Students' satisfaction linear regression analysis

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